Dr Ioannis Kosmidis

Software

Bias reduction for Binomial-response
Generalized Linear Models

Overview:

brglm provides a
unified interface for estimation in
binomial-response GLMs. Estimation can be
performed using either an adjusted-score
approach to bias reduction or maximum
penalised likelihood, where the likelihood
function is penalised by Jeffreys invariant
prior, or simply maximum likelihood. The
adjusted-score functions approach is the
most appealing because the resultant
estimator has zero bias to second order and
smaller variance, and the bias-reduced
estimates are always finite. Furthermore,
brglm contains the tools for the
construction of confidence intervals for
the resultant estimates.

Tools for profiling inference functions
for various model classes

Overview:

profileModel
provides tools that can be used to
calculate, evaluate, plot and use for
inference the profiles
of arbitrary
inference
functions for arbitrary 'glm'-like fitted
models with linear predictors. In addition,
it allows the developers of fitting
procedures to use these capabilities by
simply writing a function for the
appropriate objective to be profiled.

Beta regression

Overview:

Beta regression for modeling beta-distributed dependent variables, e.g., rates and proportions.
In addition to maximum likelihood regression (for both mean and precision of a beta-distributed response),
bias-corrected and bias-reduced estimation as well as finite mixture models and recursive partitioning
for beta regressions are provided.

Various tools
that I developed for specific purposes or
published work of mine appear in this
section. They are distributed under GPL 2
or greater in the hope that they might be
useful to someone else. Please feel free to
sent me any comments, and/or suggestions
for improvement.